Generating Explanatory Paths for Predicted Column Annotations

2. The computer-implemented method of claim 1, further comprising generating the explanatory path from the column to the determined label by selecting a path corresponding to a lowest cumulative distance score from the cumulative distance scores corresponding to the set of paths.

3. The computer-implemented method of claim 1, further comprising generating the explanatory path from the column to the determined label by selecting one or more paths from the set of paths based on the cumulative distance scores and relational edge sequence diversities corresponding to the set of paths.

4. The computer-implemented method of claim 1, wherein the explanatory path comprises a representation of a relational edge sequence, corresponding to a selected path from the set of paths, between the column, one or more neighbor nodes from the selected path, and the determined label within the knowledge graph.

6. The non-transitory computer-readable medium of claim 5, further storing instructions that, when executed by the at least one processor, cause the computer device to generate the knowledge graph by encoding the one or more column features, the one or more relational edges, and the one or more candidate labels in a latent space.

8. The non-transitory computer-readable medium of claim 5, further storing instructions that, when executed by the at least one processor, cause the computer device to generate the explanatory path from the column to the determined label by selecting a path corresponding to a lowest cumulative distance score from the cumulative distance scores corresponding to the set of paths.

9. The non-transitory computer-readable medium of claim 5, further storing instructions that, when executed by the at least one processor, cause the computer device to generate the explanatory path from the column to the determined label by selecting one or more paths from the set of paths based on the cumulative distance scores and relational edge sequence diversities corresponding to the set of paths.

12. The non-transitory computer-readable medium of claim 5, further storing instructions that, when executed by the at least one processor, cause the computer device to generate the explanatory path from the column to the determined label by selecting a threshold number of paths from the set of paths based on the cumulative distance scores corresponding to the set of paths.

13. The non-transitory computer-readable medium of claim 5, wherein the explanatory path comprises a representation of a relational edge sequence, corresponding to the selected path, between the column, one or more neighbor nodes from the selected path, and the determined label within the knowledge graph.

14. The non-transitory computer-readable medium of claim 5, further storing instructions that, when executed by the at least one processor, cause the computer device to provide, for display via the user interface of the client device, the explanatory path indicating multiple paths to the determined label.

16. The system of claim 15, wherein the one or more server devices are configured to cause the system to determine the label for the column utilizing the knowledge graph by utilizing annotation distance scores between the column and the one or more candidate labels within the knowledge graph, wherein the knowledge graph comprises an encoding of the column, the one or more column features, the one or more relational edges, and the one or more candidate labels in a latent space.

20. The system of claim 15, wherein the explanatory path comprises a representation of a relational edge sequence, corresponding to the selected path, between the column, one or more neighbor nodes from the selected path, and the determined label within the knowledge graph.